Public Internet Data Mining Methods in Instructional Design, Educational Technology, and Online Learning Research
We describe the benefits and challenges of engaging in public data mining methods and situate our discussion in the context of studies that we have conducted. Practical, methodological, and scholarly benefits include the ability to access large amounts of data, randomize data, conduct both quantitative and qualitative analyses, connect educational issues with broader issues of concern, identify subgroups/subpopulations of interest, and avoid many biases. Technical, methodological, professional, and ethical issues that arise by engaging in public data mining methods include the need for multifaceted expertise and rigor, focused research questions and determining meaning, and performative and contextual considerations of public data. As the scientific complexity facing research in instructional design, educational technology, and online learning is expanding, it is necessary to better prepare students and scholars in our field to engage with emerging research methodologies.
KeywordsPublic internet data mining Innovative methods
Compliance with Ethical Standards
This article does not report on a study with human participants performed by any of the authors.
Conflict of Interest
Royce Kimmons declares that he has no conflict of interest. George Veletsianos declares that he has no conflict of interest.
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